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Influence of δ p-doping on the behaviour of GaAs/AlGaAs SAM-APDs for synchrotron radiation

2017· article· en· W2768687647 on OpenAlexaff
T. Steinhartova, C. Nichetti, M. Antonelli, G. Cautero, R.H. Menk, A. Pilotto, F. Driussi, Pierpaolo Palestri, L. Selmi, Konstantin Koshmak, S. Nannarone, F. Arfelli, Simone Dal Zilio, G. Biasiol

Bibliographic record

VenueJournal of Instrumentation · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsUniversity of Saskatchewan
FundersMinistero dell’Istruzione, dell’Università e della Ricerca
KeywordsAvalanche photodiodeDopingOptoelectronicsMaterials scienceMultiplication (music)Molecular beam epitaxyAbsorption (acoustics)Noise (video)Synchrotron radiationLayer (electronics)OpticsDetectorEpitaxyPhysicsNanotechnologyComputer science

Abstract

fetched live from OpenAlex

Thiswork focuses on the development and the characterization of avalanche photodiodes
\nwith separated absorption and multiplication regions grown by molecular beam epitaxy. The i-GaAs
\nabsorption region is separated from the multiplication region by a δ p-doped layer of carbon atoms,
\nwhich ensures that after applying a reverse bias, the vast majority of the potential drops in the
\nmultiplication region. Therein, thin layers of AlGaAs and GaAs alternate periodically in a socalled
\nstaircase structure to create a periodic modulation of the band gap, which under bias enables
\na well-defined charge multiplication and results in a low multiplication noise. The influence of the
\nconcentration of carbon atoms in the δ p-doped layer on the device characteristics was investigated
\nand experimental data are presented together with simulation results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.310
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2017
Admission routes1
Has abstractyes

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